Proceedings of the international conference on Mathematical foundations of programming semantics
Semantic interpretation and the resolution of ambiguity
Semantic interpretation and the resolution of ambiguity
Contexts: a formalization and some applications
Contexts: a formalization and some applications
Contextual grammars and formal languages
Handbook of formal languages, vol. 2
Language theory and molecular genetics: generative mechanisms suggested by DNA recombination
Handbook of formal languages, vol. 2
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Marcus Contextual Grammars
Handbook of Formal Languages
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
On the sentence valuation in a semiring
Information Sciences—Informatics and Computer Science: An International Journal
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Fundamenta Informaticae
Context representation and fusion via likelihood masks for target tracking
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
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A rather common way of formalizing contexts as first class objects starts from the basic relation ist(c,p) which asserts that the proposition p is true in the context c. However, the space in which terms take values may itself be context-sensitive. Our aim is to introduce contexts as abstract mathematical entities in a more general framework which includes context-sensitivity, namely knowledge represented by contextual information systems. Making use of some concepts from the Rough Set Theory we refine two relations: the indiscernibility relation between the objects and the similarity relation between the contexts within a contextual information system. Both relations are illustrated with examples showing how contextual information systems can express in a natural way a very few well known phenomena. Based on these relations we propose a simple strategy for decreasing the ambiguity of contextual information systems.